The location of research sites was deemed to be very important if the research was to be representative of the whole country. This was done to avoid being bias in data collection. Considering all these factors, Lusaka and Copperbelt provinces were adopted as areas of study particularly in the three cities i.e. Lusaka, Kitwe and Ndola; and the town of Kalulushi. NGOs (Self-Help housing organizations): The country has a lot of NGOs (Non-Government­al Organization which are involved in various activities but the focus of this study will be on NGOs that are/were involved with self-help housing projects. As established earlier, these organizations may act as facilitating organizations which assist the participants through advice, support and training. In order for these organizations to be successful in their operation with self-help housing, they should have the capacity in terms of staff and equipment to undertake such projects (Anon). The study will aim to analyze this capacity, their operation in this country and the difficulties they have encountered. The Local Authority: The local authorities have an important part to play in this study and therefore, they can not be left out. Even before land is provided, they have to authorize the development to take effect. The local authority upon approval of the project can provide land and basic infrastructure which may include roads, sewer services, water services
Case Study - Influencing Others Influencing Others The greeting card incorporation, Celebrations, is expanding their company to the online market (Hill, 2004). The organization has added team member, Rebecca, as the e-Commerce Director. Rebecca is new to the company, but has experience in the web-marketing field. Rebecca’s only current problem is the lack of connectedness with her new team. The team is completed by four other directors from finance, marketing, product development, and sales. The Awaken Group proposed a leadership model on global leadership in which influence is a key pillar (2012). The case study presented by Hill (2004) suggests a lack in influential leadership on Rebecca’s part. Communication is a component that leads to successful influence with others and Rebecca’s communication with the other directors is minimal (Blanchard, 2010). The article by Kang (2012) provides a visual concept, Figure 1, which can be used to follow Rebecca’s progress. Looking at Rebecca in the three areas the figure suggests; vision, followership, and especially influence, will gage her leadership abilities. Research will be presented to support growth within Celebrations through the new idea influence presented by Rebecca. Rebecca proposes two new ideas to her team directors. The ideas are continually put down. Rebecca attempts to gain the team’s support, but lacks the ability to sway their product
A Case Study
Table of Contents
Housing – A Multisided Platform (MSP) 5
What Housing Did Right? 5
Service Package To Home Buyers – Demand Side 5
Service Package To Real Estate Agents/Brokers – Supply Side 7
Housing’s Service Characteristics 9
How Housing Tracks Service Quality? 10
What Went wrong in terms of Service? 12
Housing (formerly called Housing.com) was started by a group of 12 IITians in 2012 with the vision to transform the online real estate sector in India.
It professed to bring greater transparency and ultimately become the most trusted real estate platform in the country. It’s approach, at the most basic level, was rooted in technology and authentic data. Backed by marquee investors like Softbank, Helion and Nexus Venture Partners, Housing was valued at about $250 million by late 2014 after having raised north of $120 million since its inception.
However, things started to go sour as the real estate market slumped even as the company spent exuberant amounts in salaries and in general operations.
There was also disagreement over the focus of the company at the top management level. With increased investor’s impetus on profitability and pressure on reducing the massive operational burn rate, the company took to cutting costs and down-sized its workforce in three rounds, which brought the total employee count from 2,500 at its peak in June 2015 to about 1,000 in June 2017. All of these factors affected the key service metrics and the company lost its footing in this competitive and fragmented market of real estate.
The valuation of company eroded to $70-$75 million and was ultimately acquired by News Corp backed real estate portal PropTiger.
This report attempts to analyze what Housing did right in terms of its service and operations which captured the imagination of 3.5 million monthly visitors on its website.
It was the first real estate portal which strongly believed in the authenticity of information - be it real photos of houses, the 360 panorama view of land plots, verified neighborhood details or the accurate mapped location of each listing. It gave users a powerful tool that allowed them to conduct a thorough home scout without actually necessitating their physical presence.
We would look at what went behind in creating this seamless experience, complete with brilliant visualization and an intuitive and user friendly interface.
The report also attempts to understand the key factors that led to its downfall from its once elevated status, such as askew engagement with its suppliers (brokers, builders, owners etc.), negligent post sales service, fall in quality of listings and lack of differentiation vis-à-vis competitors.
Though Housing rode up on the credence of great design backed by data, it failed to gain the single-most thing that it stood for: the trust of its suppliers & users, more salient in a high value & low frequency transaction lik.....[read full text]
The process involves legal documents provided by the buyer and seller while a transaction takes place.
Authenticity of data
Housing is the first and only real estate website in India with a highly trained data-collection team (500 data collectors across 6 cities) that visits each and every property that it lists.
They collect and verify information, photos and geographic locations down to the last detail to ensure a great virtual profile for all the listings on the site. The ingrained belief is to provide genuine data for users and hence genuine leads for the partner brokers. This makes sure the process is hassle free and has a high rate of conversion.
Reliability of data
The data is up-to-date since Housing runs a decay algorithm in backend which automatically deactivates rental properties after 3 months and resale properties in 6 months, thereby ensuring that the flats that users can see are actually those inventory which are available in the market and aren’t yet sold out.
Unlike other portals, Housing believes in keeping the details of the users private and secure.
In an industry, where buyer leads are churned multiple times and shared to multiple brokers at the same time in the pursuit of maximum value, the experience of the house hunter takes a big hit when he is at the receiving end of a barrage of unwanted calls. However, through Housing, the user/buyer lead is passed on only to that owner/broker on whose listing that particular lead was dropped.
The convenience of shortlisting properties according to one’s requirement as well as comparing two shortlisted ones vis-a-vis certain criteria gives users the ease of browsing through large quantity of listed inventory, and hence quickly zero on the perfect flat which suits his interests.
It reduces the hassle involved in the traditional house hunting process, which involves going from one house to another and then finalising on one flat.
Housing provides a clean interface which looks slicker than other classified portals.
The creativity of the portal like 360 panorama view of land plots, verified neighbourhood details or accurate mapped location of each listing highlights the elegance in presentation.
Service Package To Real Estate Agents/Brokers – Supply Side
Paid brokers are given a feeling of exclusivity by giving them locality-level demand trends, preferential visibility, higher number of organic leads, and flexibility to update prices.
If a broker uploads a property, Housing ensures that it doesn’t display the exact address on the flat on the portal.
Though a user can get to see the locality and the neighbouring areas on the map, he won’t know the street level data. This ensures that other brokers can’t poach the same flat from the owner. Hence, the data given by the broker remains secure even as its open for everyone to see.
The most prized asset of a broker is its personal brand in its operational region.
Even if the broker is not dependent on any web portal for his business, as most part of that is dependent on his network, references and walk-ins; still he would want to maintain an online presence in all the top portals just so that his personal visibility remains high across all platforms.
Housing employs user engagement metrics such as bounce rate (% of visitors who quit after landing the first page), average daily time spent on site, click to lead conversion ratio etc. as the indicators of service quality on the demand side.
In 2014, Housing was doing better than its competitors in all the key engagement metrics as depicted below:
On the supply side, broker engagement is measured through operational metrics such as percentage of monthly active brokers (unique brokers who listed property in that given month), time spent on Housing for Agents App, the number of properties listed vis-à-vis competitors in a locality, paid packages bought etc.
Moreover, internal quality check of data collection team is done through performance metrics like number of tickets (quality escalations due to errors), efficiency (average # of flats collected per day), broker touch rate (unique brokers who gave flats) etc. Moreover, the quality of data collected in terms of the photo clarity, information integrity etc. is inspected by a 50 membered quality team which doesn’t allow a property to go live until the data collector recollects the same property according to the set guidelines.
Also an audit team is set in place which ensures that no data collector or broker is able to circumvent the system and post a f.....
This rejection of properties alienates the brokers who had to spend considerable time and effort sourcing the flats. Moreover, if any of such flats escapes the quality check (such instances increased exponentially once volume increased), the user who comes to the site sees a below-par inventory and the search experience takes a hit.
Delivery Gap (Gap 3)
The lead delivery to brokers had two major faults.
First, the mobile ‘Housing Broker App’ which was launched for the sole of purpose of tracking leads (their details, requirements, last contacted etc.) and managing properties met with lot of technical snags in the first one year of launch, resulting in cases like leads getting lost etc. Secondly, there is no system to control the flow of leads such that a good property (in terms of possession date, newness of building etc.) in a high demand locality (in terms of affordability, accessibility etc.) causes a flood of requests to one broker which is beyond his capacity to service.
Many a times, such high demand property would be long gone before the property is decayed from the system and the leads stop flowing in. This creates chagrin at both sides, brokers getting irritated by non-stop calls for a property that doesn’t exist and users getting dissatisfied by non-responsiveness by such brokers. On the other hand, there are brokers sitting disgruntled who don’t have enough leads and could have given better service to the user by leveraging his broker network.